He Haifang, Wang Hongrui, Lin Hui, Zheng Kan, Zhang Puwei
School of Geography and Environment, Jiangxi Normal University, Nanchang, 330022, Jiangxi Province, China.
College of City Construction, Jiangxi Normal University, Nanchang, 330022, Jiangxi Province, China.
Heliyon. 2024 Sep 18;10(18):e38060. doi: 10.1016/j.heliyon.2024.e38060. eCollection 2024 Sep 30.
The advantageous geographical location of the middle reaches of the Yangtze River (YRMR) plays an important role in promoting high-quality development in China and accelerating the development of the Yangtze River Economic Belt(YREB). In the new stage of development, green development efficiency (GDE) is an important metric for assessing the balance between economic development and ecological civilization. Therefore, taking three city clusters in China's YRMR as the study area, this research employs the Super-SBM model to assess their GDE in 2010-2020 in order to analyze the problem of GDE at the city scale. On this basis, spatio-temporal analyses, dynamic evolution, and convergence analyses have been carried out using the Thiel index, GML index model, and convergence model. The findings indicate that overall GDE has not yet reached an effective level and generally exhibits a two-stage fluctuating upward trend. Spatially, the pattern of distribution is "high in the southwest, low in the northeast". The differences within the city clusters in the YRMR in terms of green development are gradually narrowing, with differences within the same regions contributing the most to overall differences. The GML index shows a trend of fluctuating growth, indicating that the overall GDE growth is in good condition. GDE has grown significantly as a result of technological advancements, with the Wuhan metropolitan area (cluster A) experiencing the fastest growth in this regard, followed by the Chang-Zhu-Tan and the Poyang Lake rim city clusters (clusters B and C). The YRMR and its three major city clusters exhibit both σ- and β-convergence patterns. The convergence of GDE is simultaneously affected by several factors, including economic development (RGDP), urbanization level (UR), industrial structure (IND), technological development (TEC), and the level of openness (LO). Regional heterogeneity also exists. The above study provides decision-making references and empirical evidence for promoting green development in China's city clusters in the YRMR and advancing the improvement of economic-environmental incongruence in this area.
长江中游地区（YRMR）优越的地理位置对推动中国高质量发展以及加快长江经济带（YREB）发展发挥着重要作用。在新的发展阶段，绿色发展效率（GDE）是评估经济发展与生态文明之间平衡的重要指标。因此，本研究以中国长江中游地区的三个城市群为研究区域，采用超效率SBM模型评估其2010 - 2020年的绿色发展效率，以分析城市尺度上的绿色发展效率问题。在此基础上，运用泰尔指数、GML指数模型和收敛模型进行了时空分析、动态演化分析和收敛分析。研究结果表明，总体绿色发展效率尚未达到有效水平，总体呈现两阶段波动上升趋势。在空间上，分布格局为“西南高、东北低”。长江中游地区城市群内部在绿色发展方面的差异正在逐渐缩小，同一区域内的差异对总体差异的贡献最大。GML指数呈现波动增长趋势，表明总体绿色发展效率增长态势良好。技术进步使得绿色发展效率显著提高，其中武汉都市圈（A集群）在这方面增长最快，其次是长株潭和鄱阳湖生态经济区城市群（B和C集群）。长江中游地区及其三大城市群呈现出σ收敛和β收敛模式。绿色发展效率的收敛同时受到多个因素的影响，包括经济发展（RGDP）、城市化水平（UR）、产业结构（IND）、技术发展（TEC）和开放水平（LO）。区域异质性也存在。上述研究为推动中国长江中游地区城市群的绿色发展以及促进该地区经济与环境不协调问题的改善提供了决策参考和实证依据。
